Evidence map›Paper›PMID 29164889›Full record

ArticleJournal of proteome research2018

Comparison of Quantitative Mass Spectrometry Platforms for Monitoring Kinase ATP Probe Uptake in Lung Cancer.

Melissa A Hoffman, Bin Fang, Eric B Haura, Uwe Rix, John M Koomen

Abstract readComparative Study
In one paragraph

Article in Journal of proteome research, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

13 citing papers in PubMed.

  1. Article
  2. Article
  3. Quantification of Peptides in Food Hydrolysate fromFoods (Basel, Switzerland) · 2025
    Article
  4. Article
  5. Article
  6. DecipheringmSystems · 2024
    Article
  7. Review
  8. Deep Learning Based MS2 Feature Detection for Data-Independent Shotgun Proteomics.Proceedings. IEEE International Conference on Bioinformatics and Biomedicine · 2022
    Article
  9. Article
  10. Review
  11. Targeted Protein Quantification Using Parallel Reaction Monitoring (PRM).Methods in molecular biology (Clifton, N.J.) · 2021
    Article
  12. Article
  13. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Melissa A HoffmanH. Lee Moffitt Cancer Center & Research Institute , Tampa, Florida 33612-9497, United States.
Bin FangH. Lee Moffitt Cancer Center & Research Institute , Tampa, Florida 33612-9497, United States.
Eric B HauraH. Lee Moffitt Cancer Center & Research Institute , Tampa, Florida 33612-9497, United States.
Uwe RixH. Lee Moffitt Cancer Center & Research Institute , Tampa, Florida 33612-9497, United States.ORCID 0000-0002-8242-2770
John M KoomenH. Lee Moffitt Cancer Center & Research Institute , Tampa, Florida 33612-9497, United States.ORCID 0000-0002-3818-1762

Funding

TRANSLATIONAL RESEARCHP30CA076292 · NCI · UNIVERSITY OF SOUTH FLORIDA · PI John L. Cleveland · 1998 to 2026
$93.5M
Harnessing beneficial off-target effects of kinase inhibitors in lung cancerR01CA181746 · NCI · H. LEE MOFFITT CANCER CTR & RES INST · PI RIX, UWE · 2015 to 2019
$2.3M
Quantification of Tyrosine Phosphorylation and Kinase Expression in NSCLCR21CA169980 · NCI · H. LEE MOFFITT CANCER CTR & RES INST · PI KOOMEN, JOHN M · 2013 to 2014
$398k
NCI NIH HHS P30 CA076292NCI NIH HHS R01 CA181746NCI NIH HHS R21 CA169980
6 · The paper itself

Abstract

Recent developments in instrumentation and bioinformatics have led to new quantitative mass spectrometry platforms including LC-MS/MS with data-independent acquisition (DIA) and targeted analysis using parallel reaction monitoring mass spectrometry (LC-PRM), which provide alternatives to well-established methods, such as LC-MS/MS with data-dependent acquisition (DDA) and targeted analysis using multiple reaction monitoring mass spectrometry (LC-MRM). These tools have been used to identify signaling perturbations in lung cancers and other malignancies, supporting the development of effective kinase inhibitors and, more recently, providing insights into therapeutic resistance mechanisms and drug repurposing opportunities. However, detection of kinases in biological matrices can be challenging; therefore, activity-based protein profiling enrichment of ATP-utilizing proteins was selected as a test case for exploring the limits of detection of low-abundance analytes in complex biological samples. To examine the impact of different MS acquisition platforms, quantification of kinase ATP uptake following kinase inhibitor treatment was analyzed by four different methods: LC-MS/MS with DDA and DIA, LC-MRM, and LC-PRM. For discovery data sets, DIA increased the number of identified kinases by 21% and reduced missingness when compared with DDA. In this context, MRM and PRM were most effective at identifying global kinome responses to inhibitor treatment, highlighting the value of a priori target identification and manual evaluation of quantitative proteomics data sets. We compare results for a selected set of desthiobiotinylated peptides from PRM, MRM, and DIA and identify considerations for selecting a quantification method and postprocessing steps that should be used for each data acquisition strategy.

Indexed as

Adenosine TriphosphateData CollectionDrug MonitoringHumansLung NeoplasmsMass SpectrometryPhosphotransferasesProtein Kinase InhibitorsProteomicsAdenosine TriphosphatePhosphotransferasesProtein Kinase Inhibitorsactivity-based protein profilinglung cancerquantitative mass spectrometrytargeted therapy

Identifiers

PMID29164889
PMCPMC6021760

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.